Ask about this productRelated genes to: DQX1 antibody
- Gene:
- DQX1 NIH gene
- Name:
- DEAQ-box RNA dependent ATPase 1
- Previous symbol:
- -
- Synonyms:
- FLJ23757
- Chromosome:
- 2p13.1
- Locus Type:
- gene with protein product
- Date approved:
- 2004-02-04
- Date modifiied:
- 2016-10-05
Related products to: DQX1 antibody
Related articles to: DQX1 antibody
- Kaposi's sarcoma (KS) is a locally aggressive, multicentric tumor. RNA-binding proteins (RBPs) are pivotal for post-transcriptional regulation in various tumors. However, the aberrantly expressed RBP genes and their regulatory patterns in KS remain unclear. This study aimed to identify relevant RBP genes in KS and assess the potential functions and molecular interactions of RPS27, a dysregulated RBP in KS tissues, METHODS: Matched KS lesions and normal control tissues from ten patients were chosen for the study. Differentially expressed genes (DEGs) were first identified by RNA-sequencing, and results were validated through an independent public RNA-seq dataset (GSE147704). Among the DEGs, RBPs were selected for further analysis, with RPS27 chosen for detailed investigation due to its dysregulation in KS tissues. RT-qPCR and immunohistochemistry were employed to validate RPS27 expression. Cellular experiments were conducted for dysregulated RPS27 to explore its functions. Additionally, improved RNA immunoprecipitation (iRIP)-seq was performed to investigate potential binding interactions of RPS27 in KS. - Source: PubMed
Publication date: 2025/02/27
Zhang JingzhanWang PengLi TingtingLuo DongQu YuanyuanDing YuanKang Xiaojing - CTCF-mediated chromatin loops create insulated neighborhoods that constrain promoter-enhancer interactions, serving as a unit of gene regulation. Disruption of the CTCF binding sites (CBS) will lead to the destruction of insulated neighborhoods, which in turn can cause dysregulation of the contained genes. In a recent study, it is found that CTCF/cohesin binding sites are a major mutational hotspot in the cancer genome. Mutations can affect CTCF binding, causing the disruption of insulated neighborhoods. And our analysis reveals a significant enrichment of well-known proto-oncogenes in insulated neighborhoods with mutations specifically occurring in anchor regions. It can be assumed that some mutations disrupt CTCF binding, leading to the disruption of insulated neighborhoods and subsequent activation of proto-oncogenes within these insulated neighborhoods. To explore the consequences of such mutations, we develop DeepCBS, a computational tool capable of analyzing mutations at CTCF binding sites, predicting their influence on insulated neighborhoods, and investigating the potential activation of proto-oncogenes. Futhermore, DeepCBS is applied to somatic mutation data of liver cancer. As a result, 87 mutations that disrupt CTCF binding sites are identified, which leads to the identification of 237 disrupted insulated neighborhoods containing a total of 135 genes. Integrative analysis of gene expression differences in liver cancer further highlights three genes: ARHGEF39, UBE2C and DQX1. Among them, ARHGEF39 and UBE2C have been reported in the literature as potential oncogenes involved in the development of liver cancer. The results indicate that DQX1 may be a potential oncogene in liver cancer and may contribute to tumor immune escape. In conclusion, DeepCBS is a promising method to analyze impacts of mutations occurring at CTCF binding sites on the insulator function of CTCF, with potential extensions to shed light on the effects of mutations on other functions of CTCF. - Source: PubMed
Publication date: 2024/02/23
Wang YihengGuo XingliNiu ZhixinHuang XiaotaiWang BingboGao Lin - Cutaneous T-cell lymphomas (CTCLs) are a kind of non-Hodgkin lymphoma that originates from skin, which is difficult to treat with traditional drugs. Human histone deacetylase inhibitors (HDACi) targeted therapy has become a promising treatment strategy in recent years, but some patients can develop resistance to the drug, leading to treatment failure. There are no public reports on whether alternative splicing (AS) and RNA binding proteins (RBP) affect the efficacy of targeted therapy. Using data from the Gene Expression Omnibus (GEO) database, we established a co-change network of AS events and RBP in CTCLs for the first time, and analyzed the potential regulatory effects of RBP on HDACi-related AS events. The dataset GSE132053, which contained the RNA sequence data for 17 HDACi samples, was downloaded and clean reads were aligned to the human GRCh38 genome by hierarchical indexing for spliced alignment of the transcripts, allowing four mismatches. Gene expression levels were evaluated using exons per million fragments mapped for each gene. Student's t-tests were performed to evaluate the significance of changes in ratios for AS events, and regulated alternative splicing events (RASEs) were defined as events with values less than 0.05. To sort the differentially expressed genes functional categories, Gene Ontology terms and Kyoto Encyclopedia of Genes and Genomes pathways were identified using the KOBAS 2.0 server. The regulatory mechanisms of the RASEs and RBPs were evaluated using Pearson's correlation coefficient. Seven indirect events of HDACi resistance or sensitivity were identified: NIR_5151_RP11-977G19.10, NIR_4557_IRAG2, NIR_11870_SUMO1, NIR_5347_ING4, NIR_17935_DNAJC2, NIR_17974_CBLL1, and NIR_422_SLC50A1. The potential regulatory relationships between RBPs and HDACi-sensitive RASEs were also analyzed. and significantly affected NIR_11870_SUMO1, suggesting a potential regulatory relationship. Additionally, may regulate NIR_5347_ING4, may regulate NIR_17935_DNAJC2, and and may regulate NIR_422_SLC5A1. Overall, our findings establish a theoretical foundation for the precise targeted treatment of CTCLs with HDACi. - Source: PubMed
Publication date: 2022/09/06
Yu ShirongZhang JingzhanDing YuanKang XiaojingPu Xiongming - RNA binding protein (RBPs) dysregulation has been reported in various malignant tumors and plays a pivotal role in tumor carcinogenesis and progression. However, the underlying mechanisms in renal cell carcinoma (RCC) are still unknown. In the present study, we performed a bioinformatics analysis using data from TCGA database to explore the expression and prognostic value of RBPs. We identified 125 differently expressed RBPs between tumor and normal tissue in RCC patients, including 87 upregulated and 38 downregulated RBPs. Eight RBPs (RPL22L1, RNASE2, RNASE3, EZH2, DDX25, DQX1, EXOSC5, DDX47) were selected as prognosis-related RBPs and used to construct a risk score model. In the risk score model, the high-risk subgroup had a poorer overall survival (OS) than the low-risk subgroup, and we divided the 539 RCC patients into two groups and conducted a time-dependent receiver operating characteristic (ROC) analysis to further test the prognostic ability of the eight hub RBPs. The area under the curve (AUC) of the ROC curve was 0.728 in train-group and 0.688 in test-group, indicating a good prognostic model. More importantly, we established a nomogram based on the selected eight RBPs. The eight selected RBPS have predictive value for RCC patients, with potential applications in clinical decision-making and individualized treatment. - Source: PubMed
Publication date: 2021/01/01
Qin XinLiu ZhengfangYan KeqiangFang ZhiqingFan Yidong - : DNA methylation acts as a key component in epigenetic modifications of genomic function and functions as disease-specific prognostic biomarkers for lung squamous cell carcinoma (LUSC). This present study aimed to identify methylation-driven genes as prognostic biomarkers for LUSC using bioinformatics analysis. : Differentially expressed RNAs were obtained using the edge R package from 502 LUSC tissues and 49 adjacent non-LUSC tissues. Differentially methylated genes were obtained using the limma R package from 504 LUSC tissues and 69 adjacent non-LUSC tissues. The methylation-driven genes were obtained using the MethylMix R package from 500 LUSC tissues with matched DNA methylation data and gene expression data and 69 non-LUSC tissues with DNA methylation data. Gene ontology and ConsensusPathDB pathway analysis were performed to analyze the functional enrichment of methylation-driven genes. Univariate and multivariate Cox regression analyses were performed to identify the independent effect of differentially methylated genes for predicting the prognosis of LUSC. : A total of 44 methylation-driven genes were obtained. Univariate and multivariate Cox regression analyses showed that twelve aberrant methylated genes (ATP6V0CP3, AGGF1P3, RP11-264L1.4, HIST1H4K, LINC01158, CH17-140K24.1, CTC-523E23.14, ADCYAP1, COX11P1, TRIM58, FOXD4L6, CBLN1) were entered into a Cox predictive model associated with overall survival in LUSC patients. Methylation and gene expression combined survival analysis showed that the survival rate of hypermethylation and low-expression of DQX1 and WDR61 were low. The expression of DQX1 had a significantly negatively correlated with the methylation site cg02034222. : Methylation-driven genes DQX1 and WDR61 might be potential biomarkers for predicting the prognosis of LUSC. - Source: PubMed
Publication date: 2020/03/05
Li RuiYin Yun-HongJin JiaLiu XiaoZhang Meng-YuYang Yi-EQu Yi-Qing